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Clarifying Regional Water Scarcity in Agriculture based on the Theory of Blue, Green and Grey Water Footprints

Author

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  • Rui Shu

    (Hohai University)

  • Xinchun Cao

    (Hohai University
    Hohai University)

  • Mengyang Wu

    (Hohai University)

Abstract

Water scarcity mitigation in regional agricultural systems contributes to water use efficiency improvement. Blue (WSIblue), green (WSIgreen) and grey (WSIgrey) water scarcity indices were proposed to describe various water stresses in detail and further determine the type of regional water scarcity. WSIblue and WSIgreen reveal resource-based water scarcities, and WSIgrey characterizes environment-based water shortages. Provincial water scarcity indices of China from 2000–2014 were calculated and analyzed in the current paper. The results indicated that the national WSI, WSIgrey, WSIblue and WSIgreen values are 0.84, 0.16, 0.39 and 0.89, respectively. China is facing a high water stress, manifested as a resource-based water shortage. Northwest and Northeast China experience a severe water quantity scarcity with high WSIblue and WSIgreen values, and the central and eastern regions exhibit a high WSIgrey value. Eastern China faces both serious resource-based and environmental water shortages. The constructed blue, green and grey water scarcity indices compensate for the inability of the existing index to determine the type of water shortage and indicate the reason for water scarcity. They also provide a targeted guiding significance for the formulation of effective measures to improve agricultural water resource management and alleviate regional water scarcity.

Suggested Citation

  • Rui Shu & Xinchun Cao & Mengyang Wu, 2021. "Clarifying Regional Water Scarcity in Agriculture based on the Theory of Blue, Green and Grey Water Footprints," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 1101-1118, February.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:3:d:10.1007_s11269-021-02779-6
    DOI: 10.1007/s11269-021-02779-6
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    References listed on IDEAS

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    1. Yifan Gu & Yi Li & Hongtao Wang & Fengting Li, 2014. "Gray Water Footprint: Taking Quality, Quantity, and Time Effect into Consideration," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3871-3874, September.
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    3. Parra-López, Carlos & Reina-Usuga, Liliana & Garcia-Garcia, Guillermo & Carmona-Torres, Carmen, 2024. "Functional analysis of technological innovation systems enabling digital transformation: A semi-quantitative multicriteria framework applied in the olive sector," Agricultural Systems, Elsevier, vol. 214(C).
    4. Huan Liu & Guangyuan Niu & Qingxiang Zhang & Yuxi Yang & Hong Yao, 2022. "Town-Level Aquatic Environmental Sensitivity Assessment Based on an Improved Ecological Footprint Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 763-777, January.
    5. Xinchun Cao & Jianfeng Xiao & Mengyang Wu & Wen Zeng & Xuan Huang, 2021. "Agricultural Water Use Efficiency and Driving Force Assessment to Improve Regional Productivity and Effectiveness," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2519-2535, June.
    6. Shen, Jinlong & Zhao, Yekun & Song, Jianfeng, 2022. "Analysis of the regional differences in agricultural water poverty in China: Based on a new agricultural water poverty index," Agricultural Water Management, Elsevier, vol. 270(C).
    7. Yunfei Feng & Yi Zhang & Zhaodan Wu & Quanliang Ye & Xinchun Cao, 2023. "Evaluation of Agricultural Eco-Efficiency and Its Spatiotemporal Differentiation in China, Considering Green Water Consumption and Carbon Emissions Based on Undesired Dynamic SBM-DEA," Sustainability, MDPI, vol. 15(4), pages 1-26, February.

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